It was known that, if data items associated with each other were displayed in the same screen, information could be provided in a manner that allows the user to search desired information easily through a GUI (Graphic User Interface). Accordingly, the user would save time and efforts required for searching information. For example, if images of the globe, transmitted from a weather satellite, were integrated and displayed as a single image data, one could easily get an overview of the geographical and/or meteorological information. It would also be possible to search the single image for an area of interest through a graphic interface. Also, unattended terminals (Kiosk) located in museums, public offices and so forth, designed to provide a huge amount of information, may do so by integrating its information into a visual image so that visitors can easily search desired information.
Quickly processing a huge amount of image data is becoming essential also in the fields of science and education. For example, in the human genome project that generates a huge amount of image data it is critical that scientists be able to easily and quickly locate information they need from the accumulated data.
The ever expanding Internet environment creates new needs for techniques of processing and searching huge image data. Particularly, the Internet II project, in progress in the U.S.A., would provide an infrastructure on which an extremely large amount of data could flow, thereby allowing provision of remote services such as telemedicine, distance education and so forth. These services are known to involve a huge amount of image data, indicating a need for methods to transmit, reproduce and to do search in a huge amount of image data.
However, combining disparate data items into a single integrated image has not been the preferred method because it would involve too much to process a huge amount of data. But this is no longer true nowadays with increased computing power and high speed communication network environment.
However, there exists other limits to displaying a huge image using conventional techniques, one of which is shown in FIG. 1. Here, the image display system is composed of a hard disk drive (1), a main memory (3) for temporarily storing data read from the hard disk drive (1), a video buffer (5) for storing the data read from the main memory (3), a screen window to display images with the help of a graphics user interface (GUI:Graphic User Interface). These elements are well known in the industry and therefore more detailed explanation will not be made. This kind of conventional image displaying system has problems. Firstly, while the image data stored in the hard disk drive (1) is temporarily stored in the main memory, the operation speed of the main memory (3) is not high enough to display a huge image. Accordingly, the main memory is a bottle neck, preventing a prompt display of the image to the screen window. The bottle neck becomes worse as the amount of data increases.
Secondly, it is impossible to provide information in a manner intuitively familiar to the user. Specifically, the users of graphical information would be provided with segmental information as part of the graphical information instead of the entirety of the graphical information. Accordingly, the information items associated with each other cannot be given in such a way that allows an easier understanding of the entirety of the graphical information.
Thirdly, it is not easy to search for information. With a conventional GUI, the users of graphical information search for desired information by inevitably performing input operations such as manipulating menu keys and so forth. Accordingly, a lot of time has to be invested in order to get the desired information.
And, it is also required to provide the individual data items as a single visual image by converting the individual data items to the integrated image in order that the graphical information is provided in a manner substantially based upon the user's experiences and intuition, making it possible to easily search the desired information from a huge amount of data.